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The research problems addressed in this article pertain to the limited understanding and insufficient availability of digital storytelling guidelines for elderly and physically impaired individuals in museum presentations. The objective of this review is to explore digital storytelling guidelines along with the latest technology in museums catering to older adults and those with mobility impairments. This literature review included databases such as Scopus, ScienceDirect, and Google Scholar, covering the period from 2000 to 2023. Researchers comprehensively examined and employed content analysis to categorize all papers into three primary themes: (1) inclusive design for museum presentations; (2) trends in technology for digital storytelling in museum presentations; (3) guidelines for digital storytelling in museum presentations. This review article could enhance understanding and promote diversity, accessibility, and motivation among two specific groups of museum visitors, both onsite and online.

Summary: Background: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. Methods: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5–179) and 100.5 in men (99.5–102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. Interpretation: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Background The Intensive Care National Audit & Research Centre (ICNARC) is an independent, not-for-profit, scientific organisation. Our mission is to help improve the quality of critical care through audit, research and education conducted with and in the interests of patients and those who care for them. ICNARC coordinates national clinical audits in adult critical care and in-hospital cardiac arrest and undertakes multicentre research studies through our Clinical Trials Unit. ICNARC has recently invested in a full website redevelopment which provided a platform to make improvements against the following Pan-UK Data Governance Steering Group Data Access Transparency Standards [1]: Open application form and guidance (Standard 1); Transparent application process and criteria (Standard 2); Consider target audience (Standard 4); and Transparency of data use and auditing (Standard 6). Introduction Our primary objective was to improve our data application processes and our data use register. The purpose of this was to ensure transparency for those applying to use ICNARC data, to ensure both the process and the public benefit of use of our data can be understood by patients and the public, and to ensure the public have a mechanism to provide feedback. Methods We developed new and improved data access forms, along with supporting documents, guidance and tools for the website, ensuring these were clear and transparent for those applying to use ICNARC data. We consulted with patients and the public about the content they felt should be included, particularly within the updated data use register, and developed this with their input. The updated data use register supports regular updates and publishing of lay summaries, technical summaries, and public benefit statements. To make the process clearer, we worked with patients and the public to design an infographic to detail how ICNARC data are used. We also incorporated case studies of public benefit and a feedback form for members of the public. Results We have used our website redevelopment as a platform to improve how we communicate our data services both to those applying to use ICNARC data, and to patients and the public. The new data services area of our website (https://icnarc.org/data-services/) ensures that it meets the Transparency Standards and has allowed us to communicate how ICNARC data are used in a clearer and more effective way. Conclusions Our updated website has received positive feedback patients and the public. We anticipate the developments will continue to improve access to data and ensure transparency in the process and the use of ICNARC data.

Summary: Background: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. We aimed to evaluate and estimate the differences in health impacts of long COVID across sociodemographic categories and quantify this in Quality-Adjusted Life-Years (QALYs), widely used measures across health systems. Methods: With the approval of NHS England, we utilised OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Findings: The total OpenPROMPT cohort consisted of 7575 individuals who consented to data collection, with which we used data from 6070 participants who completed a baseline research questionnaire where 24.6% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a higher likelihood or odds of reporting loss in quality-of-life (Odds Ratio (OR): 4.7, 95% CI: 3.72–5.93) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 17.7, 95% CI: 10.37–30.33) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Interpretation: We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).